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Information-Neutral Hedging of Derivatives Under Market Impact and Manipulation Risk

Author

Listed:
  • Alimoradian, Behzad
  • Barigou, Karim

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Eyraud, Anne

Abstract

The literature on derivative pricing in illiquid markets has mostly focused on computing optimal hedging controls, but empirical microstructure studies show that large order flow generates persistent and predictable price effects. Therefore, these controls can themselves induce endogenous market manipulation because traders can internalize the impact of their own trades. We identify the key shortcoming as the absence of a formal separation between a large trader’s informational advantage and the mechanical price impact and temporary cost-of-hedging. To address this gap, we introduce a counterfactual informed observer—an agent who knows the large trader’s strategy but does not face trading frictions—and use this device to isolate informational order-flow effects from mechanical price impact, a distinction explicitly observed in microstructure data. We prove the existence of information-neutral probability measures under which the discounted asset is a martingale for this observer and derive a hedging framework that jointly accounts for transaction costs and permanent market impact. Numerical experiments show that because price pressure and order-flow effects create non-linear execution costs, the optimal hedge for an out-of-the-money call can deviate substantially from the Black–Scholes hedge, with implications for risk management and regulatory monitoring.

Suggested Citation

  • Alimoradian, Behzad & Barigou, Karim & Eyraud, Anne, 2026. "Information-Neutral Hedging of Derivatives Under Market Impact and Manipulation Risk," LIDAM Reprints ISBA 2026010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  • Handle: RePEc:aiz:louvar:2026010
    DOI: https://doi.org/10.3390/ijfs14010002
    Note: In: International Journal of Financial Studies, 2026, vol. 14(1), 2
    as

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